Operations Leadership, Generative AI

Posted 3 Days Ago
Be an Early Applicant
2 Locations
232K-290K Annually
1-3 Years Experience
Artificial Intelligence • Big Data • Machine Learning
The Data Platform for AI: High quality training and validation data for AI applications.
The Role
Lead the team building and delivering datasets for Scale's Generative AI business unit. Manage cross-functional projects, develop new products, execute data generation operations, and oversee team career paths. Strong technical background and 2+ years of leadership experience required. Strong problem-solving capabilities and entrepreneurial mindset desired.
Summary Generated by Built In

Scale's Generative AI business unit is less than one year old and is currently seeing historic levels of growth. As an Operations Leader, you will lead the team that builds and delivers datasets for our customers for one of the Gen AI verticals. This is a demanding role, and you should be prepared to wear many hats such as Operator, Product Manager and customer-facing Engagement Manager. The ideal leader should have a strong entrepreneurial mindset, be comfortable getting into the weeds, and be excited about intense, impactful work that leads to an accelerated career progression. 

Responsibilities:

  • Lead cross-functional projects with diverse stakeholders (Engineering + Ops + Go-to-Market.)
  • Develop new products or enhance existing ones to fulfill the needs of strategic customers or initiatives.
  • Own the execution of our data generation operations for strategic projects.
  • Manage a team of highly driven operators and be responsible for their career paths in the company.
  • Give regular progress updates to Scale's executive team.
  • Work on some of the most impactful problems at the company.

Requirements:

  • Strong technical background (a degree in computer science is ideal, and at minimum the role requires the ability to do data analytics using SQL or Python.)
  • 2+ years of experience leading a team, developing product or operational processes, or as a SWE.
  • Strong problem solving capabilities (experience working on operational challenges or as a consultant is a plus.)
  • Entrepreneurial experience and mindset - you are excited about building things from scratch.

Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.

Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:

$232,000-$290,000 USD

PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.

About Us:

At Scale, we believe that the transition from traditional software to AI is one of the most important shifts of our time. Our mission is to make that happen faster across every industry, and our team is transforming how organizations build and deploy AI. Our products power the world's most advanced LLMs, generative models, and computer vision models. We are trusted by generative AI companies such as OpenAI, Meta, and Microsoft, government agencies like the U.S. Army and U.S. Air Force, and enterprises including GM and Accenture. We are expanding our team to accelerate the development of AI applications.

We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an affirmative action employer and inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. 

We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information.

We comply with the United States Department of Labor's Pay Transparency provision

PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants' needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

Top Skills

Python
SQL
The Company
San Francisco, CA
523 Employees
On-site Workplace
Year Founded: 2016

What We Do

Scale accelerates the development of AI applications by helping machine learning teams generate high-quality ground truth data. Our advanced LiDAR, image, video and NLP annotation APIs allow machine learning teams at companies like OpenAI, Lyft, Pinterest, and Airbnb focus on building differentiated models vs. labeling data.

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